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环境质量、气候指标与新冠疫情：来自美国受影响最严重的十个州的见解

Environmental quality, climate indicators, and COVID-19 pandemic: insights from top 10 most affected states of the USA.

作者信息

Bashir Muhammad Farhan, Shahzad Khurram, Komal Bushra, Bashir Muhammad Adnan, Bashir Madiha, Tan Duojiao, Fatima Tehreem, Numan Umar

机构信息

Accounting School, Hubei University of Economics, Wuhan, China.

Business School, Central South University, Changsha, (410083), Hunan, People's Republic of China.

出版信息

Environ Sci Pollut Res Int. 2021 Feb 25;28(25):32856-65. doi: 10.1007/s11356-021-12646-x.

DOI:10.1007/s11356-021-12646-x
PMID:33634403
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7906571/
Abstract

In the current context of the COVID-19 pandemic, researchers are working with health professionals to inform governments on how to formulate health strategies. In this study, we examine the correlation between environmental and climate indicators and COVID-19 outbreak in the top 10 most affected states of the USA. In doing so, PM, temperature, humidity, environmental quality index, and rainfall are included as crucial meteorological and environmental factors. Kendall and Spearman rank correlation coefficients, quantile regression, and log-linear negative binominal analysis are employed as an estimation strategy. The empirical estimates conclude that temperature, humidity, environmental quality index, PM, and rainfall are significant factors related to the COVID-19 pandemic in the top 10 most affected states of the USA. The empirical findings of the current study would serve as key policy input to mitigate the rapid spread of COVID-19 across the USA.

摘要

在当前新冠疫情的背景下，研究人员正与卫生专业人员合作，为政府提供有关如何制定卫生战略的信息。在本研究中，我们考察了美国受影响最严重的10个州的环境和气候指标与新冠疫情爆发之间的相关性。在此过程中，将颗粒物、温度、湿度、环境质量指数和降雨量作为关键的气象和环境因素纳入考量。采用肯德尔和斯皮尔曼等级相关系数、分位数回归以及对数线性负二项式分析作为估计策略。实证估计得出结论，温度、湿度、环境质量指数、颗粒物和降雨量是与美国受影响最严重的10个州的新冠疫情相关的重要因素。本研究的实证结果将作为关键的政策依据，以减缓新冠病毒在美国的快速传播。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ffe/7906571/699a8619b972/11356_2021_12646_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ffe/7906571/5c00146e5df7/11356_2021_12646_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ffe/7906571/a29328676d69/11356_2021_12646_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ffe/7906571/699a8619b972/11356_2021_12646_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ffe/7906571/5c00146e5df7/11356_2021_12646_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ffe/7906571/a29328676d69/11356_2021_12646_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ffe/7906571/699a8619b972/11356_2021_12646_Fig3_HTML.jpg

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[1]
Environmental quality, climate indicators, and COVID-19 pandemic: insights from top 10 most affected states of the USA.

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[1]
Conditioning factors in the spreading of Covid-19 - Does geography matter?

Heliyon. 2024-2-3

[2]
Exploring spatiotemporal pattern in the association between short-term exposure to fine particulate matter and COVID-19 incidence in the continental United States: a Leroux-conditional-autoregression-based strategy.

Front Public Health. 2023

[3]
The Nexus Between COVID-19 Factors and Air Pollution.

Environ Health Insights. 2023-4-12

[4]
What are the Effects of Climate Variables on COVID-19 Pandemic? A Systematic Review and Current Update.

Adv Biomed Res. 2023-2-25

[5]
Association of Meteorological Factors With COVID-19 During Harmattan in Nigeria.

Environ Health Insights. 2023-2-23

[6]
The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis.

Trop Med Infect Dis. 2023-1-26

[7]
Explaining the higher COVID-19 mortality rates among disproportionately Black counties: A decomposition analysis.

SSM Popul Health. 2023-6

[8]
Impact of meteorological factors and population density on COVID-19 pandemic in Saudi Arabia.

Saudi J Biol Sci. 2023-2

[9]
Association Between Weather Parameters and SARS-CoV-2 Confirmed Cases in Two South African Cities.

Geohealth. 2022-11-1

[10]
Understanding the COVID-19 pandemic prevalence in Africa through optimal feature selection and clustering: evidence from a statistical perspective.

Environ Dev Sustain. 2022-8-30

本文引用的文献

[1]
Nexus Between the COVID-19 Dynamics and Environmental Pollution Indicators in South America.

Risk Manag Healthc Policy. 2021-1-8

[2]
Analysis of environmental taxes publications: a bibliometric and systematic literature review.

Environ Sci Pollut Res Int. 2021-4

[3]
Is the weather-induced COVID-19 spread hypothesis a myth or reality? Evidence from the Russian Federation.

Environ Sci Pollut Res Int. 2021-1

[4]
Study of COVID-19 pandemic in London (UK) from urban context.

Cities. 2020-11

[5]
Investigating the Effects of Meteorological Parameters on COVID-19: Case Study of New Jersey, United States.

Environ Res. 2020-8-30

[6]
Fluctuations in environmental pollutants and air quality during the lockdown in the USA and China: two sides of COVID-19 pandemic.

Air Qual Atmos Health. 2020

[7]
A brief review of socio-economic and environmental impact of Covid-19.

Air Qual Atmos Health. 2020

[8]
Co-variance nexus between COVID-19 mortality, humidity, and air quality index in Wuhan, China: New insights from partial and multiple wavelet coherence.

Air Qual Atmos Health. 2020

[9]
Assessment of lockdown effect in some states and overall India: A predictive mathematical study on COVID-19 outbreak.

Chaos Solitons Fractals. 2020-10

[10]
Changes in air pollution levels after COVID-19 outbreak in Korea.

Sci Total Environ. 2020-8-4

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